자료유형  

 학위논문

Control Number  

0017162911

International Standard Book Number  

9798384211426

Dewey Decimal Classification Number  

363.34

Main Entry-Personal Name  

Doty, Christopher J.

Publication, Distribution, etc. (Imprint  

[S.l.] : The Pennsylvania State University., 2024

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2024

Physical Description  

193 p.

General Note  

Source: Dissertations Abstracts International, Volume: 86-03, Section: A.

General Note  

Advisor: Giacobe, Nicklaus A.

Dissertation Note  

Thesis (Ph.D.)--The Pennsylvania State University, 2024.

Summary, Etc.  

요약The use of social media platforms has opened up a new avenue for information gathering by those in the emergency management field. This dissertation examines the use of this new source of information and seeks to add to the Crisis Informatics field of research.To do so, semi-structured interviews were conducted with members of the Emergency Management community. These individuals play a vital role in the disaster response and recovery process. They have the responsibility of providing information, gathering resources, and coordinating response efforts when disaster strikes. The aim of these interviews was to discover what information these emergency managers believed could be obtained from social media in order to aid in their operations. The coding of the interview transcripts found a set of "information categories" that appeared across the responses of the participants that made up the sample. These categories have been used to describe the types of information the emergency managers indicated as being useful. From there, the categories are used to justify a list of design considerations that future researchers should consider when designing social media analysis tools.Alongside the creation of design considerations was the development of different prototyped social media data analysis tools. This development was completed to attempt to conduct real time analysis of social media data. These tools utilized the Natural Language Processing methods of sentiment analysis, named entity recognition, and term frequency analysis. When applied to various datasets of collected Tweets, a potential example of event detection was created.

Subject Added Entry-Topical Term  

Emergency preparedness.

Subject Added Entry-Topical Term  

Black Lives Matter movement.

Subject Added Entry-Topical Term  

Evacuations & rescues.

Subject Added Entry-Topical Term  

Web studies.

Subject Added Entry-Topical Term  

Public administration.

Subject Added Entry-Topical Term  

Sociology.

Added Entry-Corporate Name  

The Pennsylvania State University.

Host Item Entry  

Dissertations Abstracts International. 86-03A.

Electronic Location and Access  

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Control Number  

joongbu:655597